3,655 research outputs found
On a Class of Fractional Obstacle Type Problems Related to the Distributional Riesz Derivative
In this work, we consider the fractional obstacle problem with a given
obstacle in a bounded Lipschitz domain in ,
such that , given by
for in ,
the dual space of the fractional Sobolev space , . The
nonlocal operator is defined
with the distributional Riesz fractional derivatives and with a measurable,
bounded, positive definite matrix ,
by .
We show that the corresponding bilinear form is a (not
necessarily symmetric) Dirichlet form that corresponds to a nonlocal integral
operator with a well defined integral kernel . We then consider
obstacle-type problems involving with one or two obstacles, as
well as the -membranes problem, thereby deriving several results, such as
the weak maximum principle, comparison properties, approximation by bounded
penalization and also the Lewy-Stampacchia inequalities, similarly to the
classical obstacle problem which is obtained at the limit . This
provides regularity of the solutions, including a global estimate in
, local H\"older regularity of the solutions when is
symmetric, and local regularity in fractional Sobolev spaces when is the
identity and corresponds to fractional
-Laplacian obstacle-type problems. These novel results are complemented with
the extension of the Lewy-Stampacchia inequalities to the order dual of
and some remarks on the associated -capacity and the
-fractional obstacle problem
On the Stability of the -Nonlocal -Obstacle Problem and their Coincidence Sets and Free Boundaries
We show that the solutions to the nonlocal obstacle problems for the nonlocal
operator, when the fractional parameter for
, converge to the solution of the corresponding obstacle problem
for , being the classical obstacle problem for the
local -Laplacian. We discuss the weak stability of the quasi-characteristic
functions of coincidence sets of the solution with the obstacle, which is a
strong convergence of their characteristic functions when under a
nondegeneracy condition. This stability can be shown also in terms of the
convergence of the free boundaries, as well as of the coincidence sets, in
Hausdorff distance when , under non-degeneracy local assumptions
on the external force and a local topological property of the coincidence set
of the limit classical obstacle problem for the local -Laplacian,
essentially when the limit coincidence set is the closure of its interior
On an anisotropic fractional Stefan-type problem with Dirichlet boundary conditions
In this work, we consider the fractional Stefan-type problem in a Lipschitz bounded domain with time-dependent Dirichlet boundary condition for the temperature , on , and initial condition for the enthalpy , given in by
where is an anisotropic fractional operator defined in the distributional sense by
is a maximal monotone graph, is a symmetric, strictly elliptic and uniformly bounded matrix, and is the distributional Riesz fractional gradient for 0 < s < 1 . We show the existence of a unique weak solution with its corresponding weak regularity. We also consider the convergence as towards the classical local problem, the asymptotic behaviour as , and the convergence of the two-phase Stefan-type problem to the one-phase Stefan-type problem by varying the maximal monotone graph .</p
Anticipated regret to increase uptake of colorectal cancer screening (ARTICS):a randomised controlled trial
Objective. Screening is key to early detection of colorectal cancer. Our aim was to determine whether a simple anticipated regret (AR) intervention could increase colorectal cancer screening uptake. Methods. We conducted a randomised controlled trial of a simple, questionnaire-based AR intervention, delivered alongside existing pre-notification letters. 60,000 adults aged 50-74 from the Scottish National Screening programme were randomised to: 1) no questionnaire (control), 2) Health Locus of Control questionnaire (HLOC) or 3) HLOC plus anticipated regret questionnaire (AR). Primary outcome was guaiac Faecal Occult Blood Test (FOBT) return. Secondary outcomes included intention to return test kit and perceived disgust (ICK). Results. 59,366 people were analysed as allocated (Intentionto- treat (ITT)); there were no overall differences between treatment groups on FOBT uptake (control: 57.3%, HLOC: 56.9%, AR: 57.4%). 13,645 (34.2%) people returned questionnaires. Analysis of the secondary questionnaire measures showed that AR had an indirect effect on FOBT uptake via intention, whilst ICK had a direct effect on FOBT uptake over and above intention. The effect of AR on FOBT uptake was also moderated by intention strength: for less than strong intenders only, uptake was 4.2% higher in the AR (84.6%) versus the HLOC group (80.4%) (95% CI for difference (2.0, 6.5)). Conclusion. The findings show that psychological concepts including anticipated regret and perceived disgust (ICK) are important factors in determining FOBT uptake. However, there was no simple effect of the AR intervention in the ITT. We conclude that exposure to AR in those with low intentions may be required to increase FOBT uptake. Current controlled trials: www.controlledtrials. com number: ISRCTN74986452
GERENCIAMENTO DE PROJETO NA INDÚSTRIA 4.0
O gerenciamento de projetos relacionado a Indústria 4.0 é considerado uma inovação que visa aumentar a probabilidade de sucesso de um determinado produto ou serviço. A nova revolução industrial afetou o meio de produção, em todo o meio organizacional. Tais mudanças forçam as empresas a buscar por ferramentas que auxiliam na gestão de projetos com o intuito de melhorar seu processo que possa lhe trazer mais agilidade sem que perca a qualidade, seja ele serviço ou produto. A pesquisa em questão apresenta, a importância do gerenciamento de projetos na indústria 4.0, destacando os pontos negativos e positivos o que leva ao insucesso e ao sucesso no projeto. Como resultados este artigo apresenta como o gerenciamento de projeto não planejado corretamente pode acarretar sérios problemas futuros, uma vez que ele é responsável pelo controle dentro da organização. É importante se atentar a forma em que é desenvolvido o trabalho da empresa que presta esse tipo de serviço, sempre analisando todos os detalhes para ver se são de ótimas qualidades e se são eficazes para a gestão no momento.
A química além dos muros da escola / Chemistry beyond school walls
A experimentação no ensino de Química é uma ferramenta didática importante para despertar o interesse dos alunos e contribuir com a aprendizagem de conceitos científicos. No entanto, os professores têm encontrado dificuldades na implantação de atividades práticas devido à falta de recursos e infraestrutura nas escolas, falta de tempo e em alguns casos, formação precária. Nesse sentido, o presente trabalho visa promover uma parceria entre o IFSP-São Roque e escolas públicas e privadas da região, a fim de divulgar o conhecimento científico e auxiliar os professores de Ciências e de Química, por meio de visitas às escolas interessadas ou recebendo seus alunos e professores nas dependências do Câmpus São Roque, para a execução de atividades práticas contextualizadas, utilizando materiais presentes no dia-a-dia. Com início em 2016, esse projeto já contou com a participação de mais de 300 alunos de escolas públicas e privadas da região de São Roque-SP. Através das avaliações realizadas ao final das visitas, foi possível verificar que os alunos e professores participantes do projeto, ficaram muito satisfeitos com as atividades realizadas e relataram interesse em participar novamente. Assim, acredita-se que esse trabalho gerou bons resultados, estreitando a relação entre a Instituição e sua comunidade local
Peritoneal function in clinical practice: the importance of follow-up and its measurement in patients. Recommendations for patient information and measurement of peritoneal function
A review is given on peritoneal function, especially ultrafiltration and ultrafiltration failure followed by recommendations on how to translate pathophysiology into clinical practice. The subsequent consequences for management of peritoneal membrane function and for patient information are also included
Incidence and diversity of the fungal genera Aspergillus and Penicillium in Portuguese almonds and chestnuts
Almonds (Prunus dulcis (Miller) D.A. Webb) and European (sweet) chestnuts (Castanea sativa Miller) are of great economic and social impact in Mediterranean countries, and in some areas they constitute the main income of rural populations. Despite all efforts to control fungal contamination, toxigenic fungi are ubiquitous in nature and occur regularly in worldwide food supplies, and these nuts are no exception. This work aimed to provide knowledge on the general mycobiota of Portuguese almonds and chestnuts, and its evolution from field to the end of storage. For this matter, 45 field chestnut samples and 36 almond samples (30 field samples and six storage samples) were collected in Trás-os-Montes, Portugal. All fungi belonging to genus Aspergillus were isolated and identified to the section level. Fungi representative of other genera were identified to the genus level. In the field, chestnuts were mainly contaminated with the genera Fusarium, Cladosporium, Alternaria and Penicillium, and the genus Aspergillus was only rarely found, whereas almonds were more contaminated with Aspergillus. In almonds, Aspergillus incidence increased significantly from field to the end of storage, but diversity decreased, with potentially toxigenic isolates belonging to sections Flavi and Nigri becoming more significant and widespread throughout storage. These fungi were determined to be moderately associated, which can be indicative of mycotoxin co-contamination problems if adequate storage conditions are not secured.P. Rodrigues was supported by grants SFRH/BD/28332/2006 from Fundacao para a Ciencia e a Tecnologia (FCT), and SFRH/PROTEC/49555/2009 from FCT and Polytechnic Institute of Braganca, Portugal
Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks
Recurrent neural networks (RNNs) are widely used in computational
neuroscience and machine learning applications. In an RNN, each neuron computes
its output as a nonlinear function of its integrated input. While the
importance of RNNs, especially as models of brain processing, is undisputed, it
is also widely acknowledged that the computations in standard RNN models may be
an over-simplification of what real neuronal networks compute. Here, we suggest
that the RNN approach may be made both neurobiologically more plausible and
computationally more powerful by its fusion with Bayesian inference techniques
for nonlinear dynamical systems. In this scheme, we use an RNN as a generative
model of dynamic input caused by the environment, e.g. of speech or kinematics.
Given this generative RNN model, we derive Bayesian update equations that can
decode its output. Critically, these updates define a 'recognizing RNN' (rRNN),
in which neurons compute and exchange prediction and prediction error messages.
The rRNN has several desirable features that a conventional RNN does not have,
for example, fast decoding of dynamic stimuli and robustness to initial
conditions and noise. Furthermore, it implements a predictive coding scheme for
dynamic inputs. We suggest that the Bayesian inversion of recurrent neural
networks may be useful both as a model of brain function and as a machine
learning tool. We illustrate the use of the rRNN by an application to the
online decoding (i.e. recognition) of human kinematics
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